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Friend@Bank Using Messenger Chatbot

During a recent dinner conversation, a friend made an interesting point about Google spending millions of dollars to deploy hundreds of thousands of servers running sophisticated algorithms to track user behavior and to deduce their likes and dislikes. Someone asked how any other company even begin to compete. Who could outspend Google to build a competing platform with such deep behavioral analytics to glean insight about their users? Then along came Facebook. It didn’t try to outdo Google on analytics (why bother with all that background analysis and inferences?). Instead, it asked the users themselves. Through a brilliantly simple “Like” button, users happily started letting Facebook know about their likes and dislikes.

While this depiction might not be completely accurate, it does provide a witty introduction to a debate on the power of the “Like” button and the implication of clicking on it. How can banks with their Facebook presence and those performing social analytics interpret click actions. With users mindlessly clicking on “Like” button participating in a continuing viral trend and potentially resulting in millions of “Likes” for a product or service, how can banks turn this into meaningful input. One could argue that liking something on Facebook might not be a reliable way to measure brand loyalty nor to infer any purchase intentions.

I believe a more effective approach would be to examine the adoption of Facebook Messenger in the business context. Facebook business pages can still be a tool for brand building and communication. However, the truly meaningful interactions would happen on Messenger. I suspect this is a possible reason why Facebook recently opened up its Messenger API for business and commerce.

Lets explore this proposition in the context of a bank wanting to build a richer dialogue with its customers on social media:

Opportunity

In my previous post on contextual banking in a digital lifestyle, I highlighted the relevance of contextual services in the banking industry. Encapsulating a banks’ services with a high degree of understanding of customer intent would create a differentiation in customer experience far beyond the strength of the services by themselves. McKinsey called this a “moment of truth” in customer service. It said what’s missing is “the spark between the customer and frontline staff members.” What if we created a personalized bank staff member at the disposal of any customer (not just wealthy ones) to carry out any such real time interactions and handle these moments I term this concept Friend@Bank.

Platform

Facebook Messenger lets banks build chatbots personifying a friendly financial advisor available to customers. How about a “friend” who is already intimately familiar with a customer’s finances that can learn about their intentions, guide them to make sound financial decisions, and help them mold their lifestyle to achieve the financial health that they desire? Instead of relying on a “Like” button, customers could explicitly share a Facebook post with the Friend@Bank on Messenger or initiate a conversation in a regular chat session.

The sophistication is built into the virtual financial advisor, an AI-assisted chatbot, to interpret these shared posts and conversations. There is no limit to the value that could be created from such interactions between human customers and their virtual assistants. We won’t soon advance anywhere close to Iron Man’s JARVIS, but we can definitely take steps in that direction.

Engagement Scenarios

Here are some representative banking-engagement scenarios.

General inquiry: This is the regular staple of any customer service on balances, payments, interest rates, products, and so on.

Affordability queries: Share items of interest to check whether or they can be purchased while staying within budget.

Example 1: I share friends’ travel posting. My Friend@Bank responds back whether I’ll be able to make a similar trip with my travel budget for the year.

Example 2: I share about elementary school posting. My Friend@Bank, who knows I have preschool kids, checks and responds if I can afford to live in that neighborhood

Goal Setting: Share items that motivate savings and to be added as goals.

Example 1: I share posts related to high ticket items such as car or home, my Friend@Bank prompts to check if I intend to setup a savings goal and plan.

Example 2: I share post about a post-retirement habit or activity, my Friend@Bank checks if my retirement planning is on track to achieve this or should I bump up my savings.

The IDEO’s Design Thinking recommends, the best solution is at the intersection of desirability, viability, and feasibility. While we should certainly strive to balance all three factors to create an optimal solution, for this exploratory thought experiment, I have only focused on the desirability factor to begin with. As I mentioned earlier, the possibilities are limitless but it is bound to happen.

Post Date: 24/01/2017

Mahesh Alampalli

About the author

Mahesh Alampalli is CTO at Texas Department of Transportation (TxDOT) with responsibilities to advance TxDOT's technology-based mission. A deep generalist with more than two decades of strategic consulting and product management experience, he brings with him a unique blend of strategy, leadership and technology skills. As an advocate of lean principles, he formed and leads NTT DATA's Community of Practice for DevOps and Continuous Delivery to bring together practitioners on lean, agile and release automation.